Impacts of energy-related CO2 emissions in China: a spatial panel data technique
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Since carbon dioxide (CO2) emissions cause great concern around the world, a large amount of literature focuses on the impact factors of CO2 emissions. However, there is little specific guidance on the spatial effects of variables and regional characteristics of CO2 emissions in China. Based on spatial panel methods, this paper used a STIRPAT (stochastic impacts by regression on population, affluence and technology) model to examine the impact of energy-related factors on CO2 emissions in China. Then, the spillover effects of China’s provincial per capita CO2 emissions have been tested. The results indicate that there exist obvious spatial correlation and spatial agglomeration features in spatial distribution of per capita CO2 emissions. Spatial economic model is demonstrated to offer a greater explanatory power than the traditional non-spatial panel model. Moreover, GDP per capita, energy intensity, industrial structure and urbanization have positive and significant effects on CO2 emissions, while the coefficient of population is not significant. According to these results, this paper proposes some policy suggestions on reducing China’s CO2 emissions.
KeywordsSpatial panel data model STIRPAT model Regional difference China
The authors gratefully acknowledge the financial supported by the National Natural Science Foundation of China (No. 71373172) and Humanities and Social Sciences Planning Fund Project of Ministry of Education (No. 15YJA790091).
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